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cs.LG2023
Normed Spaces for Graph Embedding
Diaaeldin Taha, Wei Zhao, J. Maxwell Riestenberg +1
Theoretical results from discrete geometry suggest that normed spaces can abstractly embed finite metric spaces with surprisingly low theoretical bounds on distortion in low dimens…
cs.LG2023
Modeling Graphs Beyond Hyperbolic: Graph Neural Networks in Symmetric Positive Definite Matrices
Wei Zhao, Federico Lopez, J. Maxwell Riestenberg +3
Recent research has shown that alignment between the structure of graph data and the geometry of an embedding space is crucial for learning high-quality representations of the data…